The Future of Work: An Organisational History Perspective

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Embargoed until 2023-06-03
Copyright: Dias, Malshika
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Abstract
Emerging technologies are radically changing the future of work. From artificial intelligence for customer support to robotics for performing surgery, the change is unprecedented in the history of most organisations. This thesis aims to understand and contribute rich, empirically informed insights into the phenomenon of the future of work in the context of emerging technologies from an organisational history perspective. The thesis comprises three related but standalone studies that discuss organisational trajectories and the implications of emerging technologies in three distinct organisational contexts. To explore this emerging and intrinsic phenomenon in organisations, this work adopts the historical narrativist approach and the qualitative case study method. The first study explores the interplay between tradition and technology at a pre-digital organisation when new technologies are introduced. The second study delves into the strategies and practices of realising historically embodied process knowledge when adopting a robotic process automation technology at a digitally reformed organisation. The third study traces the evolution of a strategic path towards technology and data driven innovation, from the foundation to the implementation of artificial intelligence technologies, at a born-digital organisation. Each of the three studies provides a distinct but complementary understanding on the role of organisational history by contributing to the theories of imprinting, organisational memory and path dependence. Collectively, the thesis studies contribute to our understanding of “how history matters” in the future of work. The thesis discussion contributes to the literature by integrating the implications of surface- and deep-level effects of emerging technologies for the future of work and how they are shaped by the distant, intermediate and immediate histories of organisations.
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Author(s)
Dias, Malshika
Supervisor(s)
Pan, Shan
Tim, Yenni
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Publication Year
2021
Resource Type
Thesis
Degree Type
PhD Doctorate
UNSW Faculty
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